Traffic control at the nuclear pore
Bibliographic record
Abstract
The proper communication between organelles is essential for many aspects of eukaryotic life. The coordination of nuclear and cytoplasmic activities in particular is of pivotal importance and depends on transport in and out of the nucleus. The material which translocates through nuclear pores is diverse; it includes numerous proteins, RNAs and large ribonucleoprotein complexes like ribosomal subunits. To ensure the correct nucleocytoplasmic distribution of these components, appropriate mechanisms have to be in place which control traffic across the nuclear envelope. A growing number of studies support the notion that transport through nuclear pore complexes is intimately linked to cell physiology. As such, it has become evident that changes in the cellular environment, either by externally applied stress, aging or disease, alter nuclear traffic. Due to the progress made in the past few years, we are now beginning to understand these processes at the molecular level. Thus, the concept emerges that stress or disease conditions correlate with signaling events which aim at the nuclear transport apparatus. Here, we summarize results from recent publications that provide evidence for the hypothesis that changes in cell physiology modulate nuclear traffic by targeting multiple transport factors. We propose that this traffic control is at least in part mediated by specific signaling events.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".